Over the last decade, psychological interventions, such as the values affirmation intervention, have been shown to alleviate the male-female performance difference when delivered in the classroom, however, attempts to scale the intervention are less successful. This study provides unique evidence on this issue by reporting the observed differences between two randomized controlled implementations of the values affirmation intervention: (a) successful in-class and (b) unsuccessful online implementation at scale. Specifically, we use natural language processing to explore the discourse features that characterize successful female students’ values affirmation essays to gain insight on the underlying mechanisms that contribute to the beneficial effects of the intervention. Our results revealed that linguistic dimensions related to aspects of cohesion, affective, cognitive, temporal, and social orientation, independently distinguished between males and females, as well as more and less effective essays. We discuss implications for the pipeline from theory to practice and for psychological interventions. © The Author(s) 2021.

This study integrates theories of achievement motivation and emotion to investigate daily academic behavior in an undergraduate online course. Using cluster analysis and hierarchical logistic regression, we analyze profiles of task values and anticipated emotions to understand expectations and completion of academic tasks over the duration of a week. Students’ task specific interest, opportunity cost, and anticipated satisfaction and regret varied across tasks and were predictive of both their expectations of task completion and actual task completion reported the following day. The results shed light on the important role of achievement motivation as situated and dynamic, highlighting the interplay between task priorities, task values, and anticipated emotions in academic task engagement. © 2021, The Author(s).

We demonstrate how motivational and behavioral processes can explain which students may be more likely to select into online (OL) than face-to-face (F2F) courses and also less likely to perform well in OL courses. Uni-versity students (n = 999) reported their reasons for OL course selection: university constraints, specific need for flexibility, general preference for flexibility, and learning preferences. Compared to F2F students, only OL stu-dents with certain self-selection reasons showed differences in motivation, behavior, and performance. Notably, OL students who said they had a specific need for flexibility created by the costs of competing responsibilities spent more time on non-academic activities (e.g., working, commuting), less time on academic activities (e.g., study groups), and ultimately performed worse when compared to F2F peers. These students were especially likely to be women, older, and part-time. We discuss implications for practice and for using demographic characteristics to control for selection effects.

To understand instruction during the spring 2020 transition to emergency distance learning (EDL), we surveyed a sample of instructors teaching undergraduate EDL courses at a large university in the southwest. We asked them how frequently they used and how confident they were in their ability to implement each of nine promising practices, both for their spring 2020 EDL course and a time when they previously taught the same course face-to-face (F2F). Using latent class analysis, we examined how behavioral frequencies and confidence clustered to form meaningful groups of instructors, how these groups differed across F2F and EDL contexts, and what predicted membership in EDL groupings. Results suggest that in the EDL context, instructors fell into one of three profiles in terms of how often they used promising practices: Highly Supportive, Instructor Centered, and More Detached. When moving from the F2F to EDL context, instructors tended to shift down in terms of their profile-for example, among F2F Highly Supportive instructors, 34% shifted to the EDL Instructor Centered profile and 30% shifted to the EDL More Detached Profile. Instructors who reported lower self-efficacy for EDL practices were also more likely to end up in the EDL More Detached profile. These results can assist universities in understanding instructors' needs in EDL, and what resources, professional development, and institutional practices may best support instructor and student experiences.

Collaborative tasks do not always promote equal learning. Varying levels of social interactions and regulation at the individual and group levels can influence knowledge construction efforts and learning success. To understand which collaboration patterns may be more conducive to learning, this study examined the relation between social exchange, regulation, and learning outcomes. Four project-based engineering undergraduate teams were audiotaped in collaborative tasks (7514 talk turns). Discourse was coded for regulation processes and types (self and socially shared regulation), and analyzed with Epistemic Network Analysis and Process Mining. We find that teams who reported more frequent social exchange engaged in shared regulation together with planning and monitoring more frequently, while teams with less exchange engaged in long durations of collaboration. Furthermore, students in teams with more engaged regulation reported enhanced beliefs in group efficacy to solve collaborative tasks. The study illustrates the potential of applying quantitative approaches to analyzing rich discourse.

Studies have demonstrated that utilizing spacing (spreading out study sessions at regular intervals) and self-testing strategies are optimal for learning. While some applied work has examined the relationship between these strategies on general academic achievement, there is still a need to explore how both spacing and self-testing are related to course-level learning outcomes. The goal of this study was to examine whether utilizing spacing and self-testing strategies was related to final course grade. Participants were asked to report the study strategies they utilized during the course. We found no relationship between using spacing strategies and final course grade. However, self-testing was significantly related to higher final course grades. The relationship between self-testing and final course grade remained significant even after accounting for demographic differences and prior academic achievement. Our results suggest that self-testing strategies can enhance learning even in a highly structured course. © The Author(s) 2018.

This data article includes information on institutional data at a large public research university in Southern California. In particular, data on undergraduate student enrollments in online and face-to-face courses during summer terms from 2014 to 2017 cumulating in 72,441 course enrollments from 23,610 undergraduate students in 433 courses is provided. This data includes additional information on the statistical models examining factors influencing student enrollment by course modality and the associations of course modality with course grades. This includes descriptive data and data derived from multi-level logistic regression analyses and multi-way fixed effects linear regression analyses. This data article is associated with the article Effects of course modality in summer session: Enrollment patterns and student performance in face-to-face and online classes [1]. (c) 2020 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons. org/licenses/by/4.0/).

The ability to regulate one's own learning is essential for success in online courses. Recent efforts have used clickstream data to create timely, fine-grained, and comprehensive measures of self-regulated learning (SRL) in online courses in an attempt to shed light on the process of SRL and to improve the identification of students who lack SRL skills and are at risk of low achievement. However, key questions remain: to what extent do these clickstream measures correspond to traditional self-reported measures about specific SRL constructs? Do these clickstream measures provide more information than existing self-reported measures in predicting course performance? This study used the clickstream data collected from a learning management system to measure two aspects of SRL: time management and effort regulation. We found that the clickstream measures were significantly associated with students' self-reported time management and effort regulation after the course. In addition, these clickstream measures significantly improved predictions of students' performance in the current and subsequent courses over predictions based on self-reported measures alone. These results provide evidence for the validity of the clickstream measures and guide the use of clickstream data to understand the process of SRL and identify students who might not be well served by taking classes online.

Online summer courses offer opportunities to catch-up or stay on-track with course credits for students who cannot otherwise attend face-to-face summer courses. While online courses may have certain advantages, participation patterns and student success in summer terms are not yet well understood. This quantitative study analyzed four years of institutional data cumulating in 72,441 course enrollments of 23,610 students in 433 courses during summer terms at a large public research university. Multi-level logistic regression models indicated that characteristics including gender, in-state residency, admission test scores, previous online course enrollment, and course size, among others, can influence student enrollment by course modality. Multi-way fixed effects linear regression models indicated that student grades were slightly lower in online courses compared to face-to-face courses. However, at-risk college student populations (low-income students, first-generation students, low-performing students) were not found to suffer additional course performance penalties of online course participation.

Self-efficacy has a strong influence on the learning and motivation of science students at the postsecondary level, especially in upper division science classes, which are key to student success in science majors. This empirical mixed methods research study (N = 205) examines the associations between students’ participation in an online preparation course and student self-efficacy in organic chemistry. Qualitative content analysis indicated that students benefited from the online preparatory course in the subsequent organic chemistry course series. The analysis of students’ clickstream data indicated that students with self-efficacy ratings in the top 10th percentile exhibited more frequent and consistent engagement with relevant course materials compared to students in the bottom 10th percentile. Notably, linear regression models indicated that participation in the online preparatory course was associated with higher long-term self-efficacy for first-generation college students. These results suggest that online preparatory courses may benefit some students’ self-efficacy in demanding science courses. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.